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Tools to Analyse RFLP Data
Provides functions to analyse DNA fragment samples (i.e. derived from RFLP-analysis) and standalone BLAST report files (i.e. DNA sequence analysis).
Explicitly Qualifying Namespaces by Automatically Adding 'pkg::' to Functions
Automatically adding 'pkg::' to a function, i.e. mutate() becomes dplyr::mutate(). It is up to the user to determine which packages should be used explicitly, whether to include base R packages or use the functionality on selected text, a file, or a complete directory. User friendly logging is provided in the 'RStudio' Markers pane. Lives in the spirit of 'lintr' and 'styler'. Can also be used for checking which packages are actually used in a project.
Quantile-Quantile Plot with Several Gaussian Simulations
Plots a QQ-Norm Plot with several Gaussian simulations.
Fit and Deploy DECORATE Trees
DECORATE (Diverse Ensemble Creation by Oppositional Relabeling
of Artificial Training Examples) builds an ensemble of J48 trees by recursively
adding artificial samples of the training data ("Melville, P., & Mooney, R. J. (2005)
Infrastructure for Data Stream Mining
A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893, NSF CMMI 1728612, and NIH R21HG005912. Hahsler et al (2017)
Create Waffle Chart Visualizations
Square pie charts (a.k.a. waffle charts) can be used to communicate parts of a whole for categorical quantities. To emulate the percentage view of a pie chart, a 10x10 grid should be used with each square representing 1% of the total. Modern uses of waffle charts do not necessarily adhere to this rule and can be created with a grid of any rectangular shape. Best practices suggest keeping the number of categories small, just as should be done when creating pie charts. Tools are provided to create waffle charts as well as stitch them together, and to use glyphs for making isotype pictograms.
Optimally Robust Estimation
R infrastructure for optimally robust estimation in general smoothly
parameterized models using S4 classes and methods as described Kohl, M.,
Ruckdeschel, P., and Rieder, H. (2010),
Embed 'SWI'-'Prolog'
Interface to 'SWI'-'Prolog', < https://www.swi-prolog.org/>. This package is normally not loaded directly, please refer to package 'rolog' instead. The purpose of this package is to provide the 'Prolog' runtime on systems that do not have a software installation of 'SWI'-'Prolog'.
Closed Testing Procedure (CTP)
This is a package for constructing hypothesis trees for treatment comparisons based
on the closure principle and analysing the corresponding Closed Testing Procedures (CTP)
using adjusted p-values. For reference, see
Marcus, R., Peritz, E, and Gabriel, K.R. (1976)
Boosting Methods for 'GAMLSS'
Boosting models for fitting generalized additive models for location, shape and scale ('GAMLSS') to potentially high dimensional data.